In my predictive analytics class, Python has been really helpful for making Excel data easier to understand. Instead of just looking at a spreadsheet, I upload my files into Google Colab and use Python to work with the data. I use tools like pandas to organize everything, and then I make graphs using matplotlib so I can actually see trends. It’s way easier to understand what’s going on when you can see it instead of just reading numbers.
I’ve used this a lot when I need to compare things or look at changes over time. Instead of building charts in Excel, I can write a little bit of code and make cleaner graphs faster. Once you get used to it, it saves time because you can reuse the same code for different assignments.
I also use Google Gemini to help me when I get stuck. If I don’t know how to write something or I get an error, I’ll use it to help fix my code or show me what to do. It’s kind of like having someone help you through it. I still make sure I understand what’s going on, but it definitely makes things quicker and less confusing.
Overall, using Python has made my class a lot easier and more interesting. Turning Excel data into graphs and having help from Gemini makes everything way more manageable.
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